Objective  To explore the combined predictive value of three diffusion magnetic resonance imaging (dMRI) techniques, namely, time-dependent diffusion magnetic resonance imaging (TDD-MRI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), and their sequence-derived parameters in the risk stratification of endometrioid endometrial adenocarcinoma (EEA).

Methods  A prospective cohort study was conducted on 200 female patients with clinically suspected endometrial carcinoma (aged (59.4±11.2) years) admitted to Tianjin Medical University General Hospital from March 2023 to August 2025. After screening in accordance with the inclusion criteria, 92 patients with EEA (aged (60.7±9.2) years) were finally enrolled and divided into a low-risk group and a high-risk group on the basis of the 2023 International Federation of Gynecology and Obstetrics risk stratification criteria. All patients underwent the above three dMRI examinations, and nine imaging parameters were obtained: cell diameter, intracellular volume fraction, extracellular diffusion coefficient, cell density, diffusion coefficient, pseudo-diffusion coefficient, perfusion fraction, mean diffusion coefficient, and mean kurtosis. Intergroup comparisons of measurement data were performed using independent samples t-test, Welch′s corrected t-test, or Mann-Whitney U test. Multivariate logistic regression analysis was used to identify independent predictors of EEA risk stratification, and a multisequence-combined prediction model was subsequently constructed. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of each MRI parameter and the multisequence-combined prediction model for risk stratification in patients with EEA.

Results  Among the 92 patients with EEA, 56 cases (60.9%) were in the low-risk group and 36 cases (39.1%) in the high-risk group. The high-risk group showed significantly higher cell density ((1.33±0.19) µm⁻¹ vs. (1.10±0.20) µm⁻¹; t=5.410) and mean kurtosis (1.19 (1.11, 1.23) vs. 1.02 (0.86, 1.13); Z=4.473) than the low-risk group. Conversely, the cell diameter (40.92 (38.61, 43.48) µm vs. 47.06 (39.43, 49.64) µm; Z=−2.268), extracellular diffusion coefficient (0.81 (0.71, 0.89) µm²/ms vs. 0.90 (0.75, 1.02) µm²/ms; Z=−3.178), diffusion coefficient (0.58 (0.56, 0.66) µm²/ms vs. 0.66 (0.57, 0.70) µm²/ms; Z=−3.992), and mean diffusion coefficient ((1.00±0.15) µm²/ms vs. (1.10±0.21) µm²/ms; t=−2.636) were significantly lower than those in the low-risk group. All the above differences were statistically significant (all P<0.05). Multivariate logistic regression analysis showed that cell density (OR=5.623, 95%CI: 1.884–16.786, P=0.002) and mean kurtosis (OR=3.795, 95%CI: 1.590–9.054, P=0.003) were independent predictors for EEA risk stratification. ROC curve analysis showed that among single MRI parameters, cell density had the highest area under the curve (AUC) for predicting EEA risk stratification (0.804 (95%CI: 0.714–0.893)). The multisequence-combined prediction model (cell density and mean kurtosis) achieved an AUC of 0.886 (95%CI: 0.821–0.952), with a sensitivity of 88.89% and a specificity of 76.79%.

Conclusion  The multisequence-combined prediction model constructed using cell density and mean kurtosis derived from TDD-MRI, IVIM, and DKI sequences has significant predictive value for risk stratification in EEA.